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The aim of this paper is to derive new near-ignorance models on the probability simplex, which do not directly involve the Dirichlet distribution and, thus, that are alternative to the Imprecise Dirichlet Model. We focus our investigation to a particular class of distributions on the simplex which is known as the class of Normalized Infinitely Divisible distributions; it includes the Dirichlet distribution as a particular case. Starting from three members of this class, which admit a closed-form expression for the probability density function, we derive three new near-ignorance prior models on the simplex, we analyse their properties and compare them with the Imprecise Dirichlet Model.
The paper is available in the following formats:
Francesca Mangili | francesca@idsia.ch | |
Alessio Benavoli | alessio@idsia.fr |
Send any remarks to isipta13@hds.utc.fr.